Cross-Spectral Image Patch Matching by Learning Features of the Spatially Connected Patches in a Shared Space

2019 ◽  
pp. 115-130
Author(s):  
Dou Quan ◽  
Shuai Fang ◽  
Xuefeng Liang ◽  
Shuang Wang ◽  
Licheng Jiao
Keyword(s):  
Image Patch ◽  
Spectral Image ◽  
Shared Space ◽  
Patch Matching

AFD-Net: Aggregated Feature Difference Learning for Cross-Spectral Image Patch Matching

2019 ◽  
Author(s):  
Dou Quan ◽  
Xuefeng Liang ◽  
Shuang Wang ◽  
Shaowei Wei ◽  
Yanfeng Li ◽  
...  
Keyword(s):  
Image Patch ◽  
Spectral Image ◽  
Feature Difference ◽  
Patch Matching

Element-Wise Feature Relation Learning Network for Cross-Spectral Image Patch Matching

2021 ◽  
pp. 1-15
Author(s):  
Dou Quan ◽  
Shuang Wang ◽  
Ning Huyan ◽  
Jocelyn Chanussot ◽  
Ruojing Wang ◽  
...  
Keyword(s):  
Image Patch ◽  
Spectral Image ◽  
Learning Network ◽  
Patch Matching ◽  
Relation Learning

scholarly journals Log-Spiral Keypoint: A Robust Approach toward Image Patch Matching

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Kangho Paek ◽  
Min Yao ◽  
Zhongwei Liu ◽  
Hun Kim
Keyword(s):  
Image Pyramid ◽  
Image Patch ◽  
Keypoint Detection ◽  
Binary Descriptor ◽  
Image Patches ◽  
High Resolution Images ◽  
Matching Performance ◽  
Computer Vision Applications ◽  
Patch Matching ◽  
Sampling Pattern

Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images. Most of keypoint methods are mainly used to match the high-resolution images, which always utilize an image pyramid for multiscale keypoint detection. In this paper, we propose a novel keypoint method to improve the matching performance of image patches with the low-resolution and small size. The location, scale, and orientation of keypoints are directly estimated from an original image patch using a Log-Spiral sampling pattern for keypoint detection without consideration of image pyramid. A Log-Spiral sampling pattern for keypoint description and two bit-generated functions are designed for generating a binary descriptor. Extensive experiments show that the proposed method is more effective and robust than existing binary-based methods for image patch matching.

Multi-relation Attention Network for Image Patch Matching

2021 ◽  
pp. 1-1
Author(s):  
Dou Quan ◽  
Shuang Wang ◽  
Yi Li ◽  
Bowu Yang ◽  
Ning Huyan ◽  
...  
Keyword(s):  
Image Patch ◽  
Attention Network ◽  
Patch Matching

Better and Faster: Exponential Loss for Image Patch Matching

2019 ◽  
Author(s):  
Shuang Wang ◽  
Yanfeng Li ◽  
Xuefeng Liang ◽  
Dou Quan ◽  
Bowu Yang ◽  
...  
Keyword(s):  
Image Patch ◽  
Patch Matching
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